| Literature DB >> 33808758 |
Amar H Kelkar1, Jodian A Blake2, Kartikeya Cherabuddi3, Hailee Cornett4, Bobbie L McKee5, Christopher R Cogle1.
Abstract
(1) Background: Vaccine hesitancy and rejection are major threats to controlling coronavirus disease 2019 (COVID-19). There is a paucity of information about the attitudes of cancer patients towards vaccinations and the role of clinical oncologists in influencing vaccination acceptance. (2)Entities:
Keywords: COVID-19; SARS-CoV2; patient education; public health; vaccine; vaccine hesitancy
Year: 2021 PMID: 33808758 PMCID: PMC8003419 DOI: 10.3390/healthcare9030351
Source DB: PubMed Journal: Healthcare (Basel) ISSN: 2227-9032
Figure 1Number of participants who completed the pre-webinar and/or post-webinar surveys.
Characteristics of webinar participants who completed surveys. Three overlapping cohorts of people (238 unique individuals) completed surveys online before or after participating in a webinar on vaccines and coronavirus. A cohort of 205 people completed the pre-webinar survey, 105 people completed both surveys, and a cohort of 138 people completed the post-webinar survey. The characteristics of race, health insurance, and connections to cancer add up to more than 100% because respondents were allowed to choose more than one answer. For other characteristics, the total may not equal 100% because of rounding.
| Pre-Webinar Survey Completed ( | Both Surveys Completed ( | Post-Webinar Survey Completed ( | ||||
|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
|
|
| ||||||
| 18–26 | 10 | 5% | 4 | 4% | 4 | 3% |
| 27–29 | 4 | 2% | 0 | 0% | 1 | 1% |
| 30–39 | 20 | 10% | 9 | 9% | 9 | 7% |
| 40–49 | 32 | 6% | 14 | 13% | 15 | 11% |
| 50–59 | 35 | 17% | 15 | 14% | 15 | 11% |
| 60–64 | 33 | 16% | 20 | 19% | 25 | 18% |
| 65–69 | 19 | 9% | 11 | 11% | 1 | 1% |
| 70–79 | 39 | 19% | 23 | 22% | 25 | 18% |
| 80 years or older | 11 | 5% | 9 | 9% | 11 | 8% |
| Prefer not to answer | 2 | 1% | 0 | 0% | 32 | 23% |
|
| ||||||
| Man | 40 | 20% | 25 | 24% | 27 | 20% |
| Woman | 161 | 79% | 78 | 74% | 88 | 57% |
| Nonbinary, genderqueer, or genderfluid | 1 | 0.5% | 1 | 1% | 0 | 0% |
| Prefer not to answer | 3 | 2% | 1 | 1% | 23 | 17% |
|
| ||||||
| Heterosexual or “straight” | 191 | 93% | 97 | 92% | 108 | 78% |
| Homosexual, gay, or lesbian | 3 | 1.5% | 2 | 2% | 3 | 2% |
| Bisexual | 2 | 1% | 0 | 0% | 1 | 1% |
| Other | 1 | 0.5% | 1 | 1% | 1 | 1% |
| Prefer not to answer | 8 | 4% | 4 | 4% | 25 | 18% |
|
| ||||||
| American Indian or Alaska Native | 2 | 1% | 0 | 0% | 1 | 1% |
| Asian or Asian American | 10 | 5% | 3 | 3% | 3 | 2% |
| Black or African American | 12 | 6% | 7 | 7% | 8 | 6% |
| Native Hawaiian or Other Pacific Islander | 1 | 0.5% | 1 | 1% | 1 | 1% |
| White | 169 | 82% | 90 | 86% | 99 | 72% |
| Other | 7 | 3% | 2 | 2% | 2 | 1 |
| Prefer not to answer | 6 | 3% | 2 | 2% | 24 | 17% |
|
| ||||||
| Hispanic or Latinx | 18 | 9% | 5 | 5% | 5 | 4% |
| Not Hispanic or Latinx | 175 | 85% | 96 | 91% | 107 | 78% |
| Prefer not to answer | 12 | 6% | 4 | 4% | 26 | 19% |
|
| ||||||
| High school or equivalent | 7 | 3% | 3 | 3% | 4 | 3% |
| Some college credits | 15 | 7% | 7 | 7% | 9 | 7% |
| Associate’s degree | 15 | 7% | 7 | 7% | 9 | 7% |
| Bachelor’s degree | 60 | 29% | 29 | 28% | 32 | 23% |
| Graduate or professional degree | 103 | 50% | 56 | 53% | 60 | 43% |
| Prefer not to answer | 5 | 2% | 3 | 3% | 24 | 17% |
|
| ||||||
| Number of people in household | ||||||
| 1 | 37 | 18% | 24 | 23% | 28 | 20% |
| 2 | 106 | 52% | 58 | 55% | 65 | 47% |
| 3 | 31 | 15% | 10 | 10% | 11 | 8% |
| 4 | 17 | 8% | 7 | 7% | 8 | 6% |
| 5 | 8 | 4% | 2 | 2% | 2 | 1% |
| 6 | 3 | 1.5% | 2 | 2% | 2 | 1% |
| 7 | 2 | 1% | 2 | 2% | 2 | 1% |
| 8 | 0 | 0% | 0 | 0% | 0 | 0% |
| 9 or more | 1 | 0.5% | 0 | 0% | 0 | 0% |
| Prefer not to answer | 0 | 0% | 0 | 0% | 20 | 14% |
| Total household income for 2020 | ||||||
| Less than $15,000 | 2 | 1% | 1 | 1% | 1 | 1% |
| $15,000 to $19,999 | 5 | 2% | 3 | 3% | 3 | 2% |
| $20,000 to $24,999 | 3 | 1.5% | 1 | 1% | 1 | 1% |
| $25,000 to $34,999 | 6 | 3% | 4 | 4% | 4 | 3% |
| $35,000 to $49,999 | 9 | 4% | 8 | 8% | 10 | 7% |
| $50,000 to $74,999 | 25 | 12% | 12 | 11% | 15 | 11% |
| $75,000 to $99,999 | 29 | 14% | 15 | 14% | 15 | 11% |
| $100,000 and above | 71 | 35% | 29 | 28% | 32 | 23% |
| Prefer not to answer | 55 | 27% | 32 | 31% | 57 | 41% |
|
| ||||||
| Employer offered | 133 | 65% | 59 | 56% | 65 | 47% |
| Private purchase | 37 | 18% | 21 | 20% | 26 | 19% |
| Medicare | 67 | 33% | 44 | 42% | 49 | 36% |
| Veterans Affairs, Tricare | 14 | 7% | 7 | 7% | 8 | 6% |
| Medicaid | 6 | 3% | 3 | 3% | 3 | 2% |
| No health insurance | 1 | 0.5% | 0 | 0% | 0 | 0% |
| Other (student health) | 7 | 3% | 3 | 3% | 8 | 6% |
| Prefer not to answer | 0 | 0% | 0 | 0% | 13 | 9% |
|
| ||||||
| Democrat | 69 | 34% | 38 | 36% | 47 | 34% |
| Republican | 39 | 19% | 19 | 18% | 19 | 14% |
| Independent | 29 | 14% | 12 | 11% | 14 | 10% |
| Other | 4 | 2% | 1 | 1% | 2 | 1% |
| Prefer not to answer | 64 | 31% | 35 | 33% | 56 | 41% |
|
| ||||||
| Have cancer and actively receiving treatment | 55 | 27% | 35 | 33% | 40 | 29% |
| Cancer survivor and not receiving treatment | 59 | 29% | 24 | 24% | 29 | 17% |
| Caregiver to a cancer patient | 20 | 10% | 12 | 11% | 12 | 9% |
| Friend or family member to a cancer patient | 47 | 23% | 25 | 24% | 27 | 20% |
| Health care provider | 39 | 19% | 15 | 14% | 15 | 11% |
| Academic researcher or research staff member | 18 | 9% | 12 | 11% | 14 | 10% |
| Government employee | 8 | 4% | 3 | 3% | 3 | 2% |
| Community-based organization that serves people with cancer | 20 | 10% | 10 | 10% | 10 | 7% |
| Health insurance company employee | 1 | 0.5% | 0 | 0% | 0 | 0% |
| No connection to cancer | 2 | 1% | 0 | 0% | 0 | 0% |
| Other (caregiver to person with other disease, for-profit business, family of health care worker) | 12 | 6% | 6 | 6% | 8 | 6% |
Figure 2Sources of information about vaccines against coronavirus disease 2019 (COVID-19).
Characteristics and beliefs associated with the intention to receive a COVID-19 vaccine. LINEAR modeling of 31 demographic and attitude variables in 205 people prior to participating in a webinar.
| Characteristic | Coefficient | Significance | Model Importance |
|---|---|---|---|
| I plan to encourage my family, friends, co-workers, and community to get a COVID-19 vaccine. | 0.260 | 0.548 | |
| I would take a COVID-19 vaccine if recommended by my doctor. | 0.252 | 0.351 |
Figure 3Predictors of the intention to receive a COVID-19 vaccine. Levels of model importance in predicting the intention to receive a COVID-19 vaccine based on webinar participant demographics and beliefs.
Figure 4Changes in beliefs and perspectives on vaccines against COVID-19 before and after a webinar. Dotted bars represent data collected before the webinar. Black bars represent data collected after the webinars. A paired t-test used to compare before and after scores. *, p < 0.05.
Figure 5Which vaccine would you take?
Figure 6Model of vaccine hesitancy or enthusiasm in cancer patients. The size of the boxes is proportionate to their frequency in the cancer population participating in a webinar on vaccines and COVID-19. The gray boxes indicate the association between factors and the plan to receive a vaccine. The factors next to the up-arrow are associated with decreasing vaccine hesitancy in the cancer population participating in a webinar.